Syndromic Surveillance: Adapting Innovations to Developing Settings

Surveillance, according to the World Health Organization (WHO), “is the cornerstone of public health security” [1]. In many developing countries, human, laboratory, and infrastructure limitations impede effective surveillance [2–5]. Such countries likely do not meet core surveillance and response capacities under the new International Health Regulations (IHR 2005) [6], which require detection of elevated disease and death rates, immediate implementation of control measures, and reporting to WHO of any event that may constitute a public health emergency of international concern [7]. (The previous IHR covered only cholera, plague, and yellow fever.) In some high-income countries, “syndromic surveillance,” a novel approach, uses pre-diagnostic data and statistical algorithms to detect epidemics earlier than traditional surveillance, including unusual diseases with nonspecific presentations [8–10] (Box 1). Syndromic surveillance also supports public health “situational awareness” [11,12], which means monitoring the effectiveness of epidemic responses and characterizing affected populations. Despite obstacles to implementation in resource-limited settings, the tools and strategies of syndromic surveillance hold promise for improving public health security in developing countries. Successful applications show that the obstacles can be overcome.